Senior Validation Engineer

Novo Nordisk A/S; Søborg, Aalborg; Remote; DKK 651,000 - 957,000; Full time

Job summary

Novo Nordisk A/S in Denmark is seeking a Senior Validation Engineer to ensure AI and data science workflows in clinical studies operate as intended, with manual and automated testing and an auditable framework.

You will design tests in Python, review code, work with Azure and Databricks, and contribute to risk-based validation, data integrity and GCP-regulated data practices. Travel is occasional.

Qualifications

• Manual and automated testing experience (Python or similar).
• Experience with Git, code review, CI/CD, reusable test automation components.
• Strong IT understanding including APIs, integrations, data-processing workflows; Azure and Databricks experience.
• Understanding of risk-based validation and data integrity.
• Proactive, investigative approach and clear written documentation of findings.
• Motivation to develop expertise in GCP-regulated clinical data science and AI evaluation.

Responsibilities

• Design, execute and document manual tests and automated tests in Python or similar, producing reproducible evidence that workflows perform as intended.
• Evaluate system architecture, integrations, cyber security and data integrity; develop validation documentation from design specs to risk assessments and user requirements.
• Build the test automation framework with reusable tests, fixtures, data generators, and CI/CD integration; keep code under version control and peer review.
• Assess open-source packages for use, considering purpose, complexity, origin, maintenance and licensing; document actions and alternatives.
• Test workflows involving omics, imaging and digital-device data; ensure input/output integrity, transformations and reproducibility.
• Collaborate with AI specialists to evaluate models against context of use, datasets, metrics and acceptance criteria; document evidence under AI governance.

Job description

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As Senior Validation Engineer, you will make sure the AI and data science workflows used in clinical studies do what they are meant to do, and can prove it. You will design and run manual and automated tests, investigate defects and build the test automation framework behind them. Your evidence protects data integrity and patient safety, and gives clinical teams results they can rely on.

What you’ll bring

A degree in computer science, data science, engineering, mathematics or a related discipline, or equivalent professional experience.

Practical experience in manual and automated testing (Python or similar), test design, debugging and defect investigation.

Experience with Git, code review, CI/CD, reusable test automation components and reproducible data analysis.

Strong IT understanding, including software architecture, APIs, integrations, execution environments and data-processing workflows, with experience in Microsoft Azure and Databricks.

An understanding of risk-based validation and data integrity, and the ability to judge whether test evidence supports a system’s intended use.

A proactive, investigative approach and clear written documentation of technical findings.

Motivation to build expertise in GCP-regulated clinical data science, AI evaluation and emerging data modalities.

Useful, but not essential

Experience with R, and numerical or statistical testing.

Experience with open-source security and licensing assessments.

Experience with AI evaluation.

What you’ll do

You will combine hands‑on validation engineering with risk‑based assessment of open-source components, working under the Novo Quality Management System (QMS) and Good Clinical Practice (GCP). Your main areas of work:

Design, execute and document manual tests (for example via the user interface) and automated tests in Python or similar, producing reproducible evidence that workflows and supporting IT/AI systems perform as intended.

Evaluate system architecture, integrations, cyber security and data integrity, and develop technical and validation documentation, from design specifications and IT risk assessments to user requirements and validation plans, so deliverables stay audit ready.

Build the team’s test automation framework with reusable tests, fixtures, test‑data generators, output checks and reporting components, and integrate them into CI/CD workflows to catch failures early. Keep test code under version control and peer review.

Assess open-source packages for intended use, considering purpose, complexity, origin, maintenance and community exposure. Screen components and dependencies for security, licensing and known defects, document required actions and recommend alternatives where needed.

Test workflows involving omics, imaging and digital‑device data, covering input and output integrity, transformations, annotations, audit trails and reproducibility.

Work with AI specialists to evaluate models against the agreed context of use, reference datasets, metrics and acceptance criteria, including bias, robustness and human‑interaction scenarios. Separate software defects from model limitations or variability, and document the evidence under applicable AI governance.

Who you’ll work with

You will join a validation team within AI & Digital Innovation, part of Research & Development.

Day to day, you will partner with data scientists, AI specialists, software developers, IT solution owners and platform teams. You will also work with data and AI governance colleagues and external partners. Close collaboration helps you agree acceptance criteria early, raise issues quickly and move from finding a defect to getting it fixed.

The role involves occasional business travel, typically 4–5 times per year, with trips lasting approximately 3–5 days. These visits will primarily support participation in conferences, knowledge‑sharing events, and in‑person collaboration with local and cross‑functional team members. The travel is intended to strengthen team alignment, foster collaboration across sites, and support professional development through engagement with the broader scientific, AI, and validation communities.

What you can expect here

You will work on validation for clinical data science and AI, an area where expectations for evidence are rising and where you can build deep expertise in GCP‑regulated work, AI evaluation and emerging data modalities. You will grow through hands‑on practice and by learning alongside colleagues from science, development, validation and quality.

You will be trusted to take ownership, make your voice heard and shape how the team tests and automates. You will be supported to perform at your best, with clear expectations for the quality of your work.

What we offer

At Novo Nordisk, you’ll join a global healthcare company with a unique culture and strong results. We offer continuous learning, career development, and benefits tailored to your life and career stage.

For this role, the Annual Base Salary ranges from 651,000.00 DKK to 956,900.00 DKK, corresponding to the level of the position

The placement within the salary range will be assessed during the recruitment process based on the candidate’s skills, competencies, knowledge, and relevant experience.

Incentives and Benefits: The salary package may include short-term and/or long‑term incentives as well as other employee benefits based on position level, location, functional area, and relevant market benchmarks.

We commit to an inclusive recruitment process and equality of opportunity for all our job applicants.